{"id":"W2071657723","doi":"10.1517/17460440903544456","title":"High-content screening for the discovery of pharmacological compounds: advantages, challenges and potential benefits of recent technological developments.","year":2010,"lang":"en","type":"article","venue":"PubMed","topic":"Cell Image Analysis Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University and Génome Québec Innovation Centre","funders":"","keywords":"Drug discovery; Data science; Biochemical engineering; High-content screening; Nanotechnology; Risk analysis (engineering); Computer science; Chemistry; Business; Engineering; Materials science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00199063,0.0008430885,0.00132063,0.002031288,0.0004451755,0.00176372,0.001043658,0.001501781,0.004589265],"category_scores_gemma":[0.001693593,0.0004503605,0.0008290388,0.001769075,0.001182791,0.002336017,0.001282929,0.002109229,0.002662715],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005767739,"about_ca_system_score_gemma":0.0008001195,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003254442,"about_ca_topic_score_gemma":0.0005787045,"domain_scores_codex":[0.9989609,0.0002616227,0.0000439885,0.0001069276,0.0005701321,0.00005651496],"domain_scores_gemma":[0.9984075,0.0010185,0.000128377,0.000136632,0.0002261556,0.00008281873],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005759011,0.0002487971,0.001399598,0.005886798,0.0002508924,0.0006877761,0.0001598593,0.001019632,0.4812048,0.01475441,0.01461519,0.4791963],"study_design_scores_gemma":[0.0001446278,0.001783007,0.009692419,0.0006661181,0.0005191014,0.009710034,0.0003192719,0.009376471,0.6493589,0.0227398,0.2954773,0.000213025],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.04033509,0.6030406,0.3208024,0.008913925,0.001607698,0.0006086359,0.001567717,0.002009448,0.02111454],"genre_scores_gemma":[0.1653,0.5002868,0.3128004,0.004758406,0.0014787,0.0005617083,0.002007061,0.0002811373,0.01252584],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004589265,"threshold_uncertainty_score":0.01535261,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04412945456407349,"score_gpt":0.2658614725586849,"score_spread":0.2217320179946114,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}